How etiological explanations for depression impact perceptions of stigma, treatment effectiveness, and controllability of depression

Abstract

Background and aims: There is controversy regarding how etiological explanations for depression, particularly biological explanations, influence perceptions of stigma, perceived controllability of depression, and perceived effectiveness of depression treatments. This study evaluated how biological and psychosocial explanations for depression relate to these variables.

Method: Undergraduate students who reported ever suffering from clinical depression (n = 36) and who reported no personal history of depression (n = 33) completed a diagnostic interview and questionnaires assessing etiology beliefs, stigma perceptions, perceived controllability of depression, and perceived effectiveness of different depression treatments.

Results: Although “ever depressed” participants perceived more stigma than “never depressed” participants, endorsing either etiological model had little relation to perceived stigma. Endorsing psychosocial explanations was associated with perceiving self-initiated treatments as effective, and self-initiated treatments were viewed as more effective than either psychotherapy or medical interventions.

Conclusions: Stigmatizing attitudes about depression appear more meaningfully related to individuals' personal experiences with depression than to etiological explanations for depression; yet etiological models appear to have important implications for treatment preference and perceived controllability of mood.

Keywords:

• Etiology beliefs
• major depression
• treatment preference
• stigma
• perceived control

Declaration of interest: The authors report no conflict of interest. The authors alone are responsible for the content and writing of the paper.

Note

1. A principal components analysis (PCA) was conducted on the 17 items from the Etiology Beliefs Survey. The PCA revealed five components with eigenvalues exceeding 1. The screeplot revealed that two components should be used for further analysis. A Varimax rotation produced a two factor solution that explained a total of 38.9% of the variance, with Component 1 (psychosocial explanations) contributing 19.51% and Component 2 (biological explanations) contributing 19.39%.